30 results about "Risk class" patented technology

A trade allocation system includes a computer system having a network interface over which messages can be exchanged with an order management system. The computer system is also coupled to a first database that stores data associating portfolios with risk classes and target ratios. A second database stores instructions to configure the system to receive from order management systems messages describing trades of financial instruments. Each message can include a financial instrument identifier, a size of the trade, and a risk class identifier. The instructions also configure the processor to query the first database to determining a portfolios that are associated with a risk class identified by a risk class identifier in a message as well as to determine a target ratio for each of the portfolios. The processor then allocates the trade of the financial instrument among each of the portfolios based on the target ratios. Allocating a trade of a financial instruments among a group of portfolios include receiving a message descriptive of a trade of a financial instrument. The message can include a financial instrument identifier and a size of the trade. A collection of portfolios are then identified based on a match between a risk class of the portfolio and the risk class of the traded financial instrument. The trade is then allocated among each of the portfolios based on a target ratio associated with each portfolio.

A risk classification technique that exploits the existing risk structure of the decision problem in order to produce risk categorizations for new candidates is described. The technique makes use of a set of candidates for which risk categories have already been assigned (in the case of insurance underwriting, for example, this would pertain to the premium class assigned to an application). Using this set of labeled candidates, the technique produces two subsets for each risk category: the Pareto-best subset and the Pareto-worst subset by using Dominance. These two subsets can be seen as representing the least risky and the most risky candidates within a given risk category. If there are a sufficient number of candidates in these two subsets, then the candidates in these two subsets can be seen as samples from the two hypothetical risk surfaces in the feature space that bound the risk category from above and below respectively. A new candidate is assigned a risk category by verifying if the candidate lies within these two bounding risk surfaces.

Methods and apparatus, including computer program products, for securitizing natural catastrophe risk. One or more risk classes representing natural catastrophe risks is are established, and a first collection of risk instruments of a first risk class of the one or more risk classes is issued. Each risk class is recurringly issuable as risk instruments providing a return on an investment. The amount of the return for a risk instrument is contingent upon the occurrence of a realization event for the corresponding represented natural catastrophe risk. Collections of risk instruments issued from recurringly issuable risk classes are also described.

An automatic risk assessment system is provided that determines a risk for the patch based on collected activity metrics, file weights, a list of files affected by the patch, and other factors. An application monitor collects metrics from the application to determine the level of activity of the application or other component to be patched. The patch may have associated therewith metadata including a list of files that will be affected by the patch. Policies may store information about how risk is to be assessed. This information may include, for example, file weights and information defining categories of risk.

A robust process for automating the tuning and maintenance of decision-making systems is described. A configurable multi-stage mutation-based evolutionary algorithm optimally tunes the decision thresholds and internal parameters of fuzzy rule-based and case-based systems that decide the risk categories of insurance applications. The tunable parameters have a critical impact on the coverage and accuracy of decision-making, and a reliable method to optimally tune these parameters is critical to the quality of decision-making and maintainability of these systems.

The invention discloses a traffic accident risk estimation method and system. According to the method and the system, a corresponding relation chain between a risk factor and a risk class is calculated and determined by acquiring an expressway tunnel traffic accident risk factor and an expressway tunnel traffic accident risk class and employing a spectral clustering algorithm; a risk estimation model is constructed according to the relation chain and an extreme learning algorithm; and the final risk class corresponding to the risk factor can be obtained by inputting arbitrary risk factor data to the risk estimation model. Therefore, with the adoption of the method or the system provided by the invention, the expressway tunnel traffic accident risk estimation efficiency is effectively improved, so that the expressway tunnel traffic accident risk estimation efficiency process is more high-efficiency and convenient, and the safety evaluation of expressway tunnel operation period is accurately and effectively achieved.

The invention provides a fault prediction method based on synthetic minority class oversampling and deep learning. The Means method is used for clustering a few types of samples in the sample set; deleting the noise class cluster after clustering; dividing the class cluster into noise class samples in each class cluster by using a KNN method; fault samples and risk samples, deleting the noise samples; and finally, inputting a random number into each class cluster, and selecting a certain sample as an output sample according to a proportional relation between the random number and the fault class sample and the risk class sample in the class cluster;realizing oversampling of the SMOTE method ; and then increasing the number of a few types of samples through multiplication operation, so thatthe types of the samples in the finally obtained fusion sample are more balanced, and the acquired feature data are balanced, thereby facilitating model training, maximally mining the law behind thedata, and realizing a better fault prediction effect.

Embodiments according to the present invention provide an Impedance-based Arc-Fault Determination Device (IADD) and method that, when attached to an electrical node on the power system and through observations on voltage, current and phase shift with a step load change, determine the effective Thevenin equivalent circuit or Norton equivalent circuit at the point of test. The device and method determine the expected bolted fault current at the test location of interest, which enables calculation of incident energy and the assignment of a flash-hazard risk category.

An automatic risk assessment system is provided that determines a risk for the patch based on collected activity metrics, file weights, a list of files affected by the patch, and other factors. An application monitor collects metrics from the application to determine the level of activity of the application or other component to be patched. The patch may have associated therewith metadata including a list of files that will be affected by the patch. Policies may store information about how risk is to be assessed. This information may include, for example, file weights and information defining categories of risk.

An automated, real-time mortality classification and signaling system for real-time risk assessment, and adjustment based on an automated selective multi-level triage process, where risks associated with a plurality of risk-exposed individuals are at least partially transferable from a risk-exposed individual to a first insurance system and from the first insurance system to an associated second insurance system, the real-time mortality classification and signaling system accesses a database stored in a memory to retrieve risk classes, identifies and selects a specific risk class associated with the risk of the exposed individual, processes specific parameters of the exposed individual using a machine learning-based pattern recognition to automatically assign risk-exposed individuals with detected non-smoking patterns to a second triage channel, and automatically assigning risk-exposed individuals with detected smoking patterns to a third triage channel as predicted smokers. Based on the classified risk, the system provides an alert notification to a third-party system.

The invention relates to an SVM-based power consumer credit risk early warning method and system, and the method comprises the steps: setting a threshold value for a power consumer credit risk basic index, and dividing risk early warning intervals of different power consumer credit risk basic indexes according to the threshold value; selecting sample data, processing the sample data, distributingcorresponding weights to the power consumer credit risk basic indexes by using a principal component analysis method, calculating a risk early warning evaluation value of the sample data, and dividingrisk categories where the risk early warning evaluation value is located according to the risk early warning evaluation value; establishing a power consumer credit risk early warning SVM model, and predicting the power consumer credit risk; and taking the obtained optimal parameter value as a parameter value of a power consumer credit risk early warning SVM model, and optimizing the power consumer credit risk early warning SVM model. According to the method, parameter optimization is carried out through the SVM classification model, the prediction accuracy for the nonlinear relationship and the small sample model is high, and a good early warning effect is achieved in credit risk early warning.

One or more portions of a text corpus indicative of operational risk from a set of risk assessment documents is identified. Contextual features from the one or more portions of the text corpus are determined by applying a natural language processing (NLP) algorithm on the one or more portions. Risk identifiers are extracted based on the determined contextual features. A risk assessment software is generated based on the extracted risk identifiers and an operational risk category.

A method for generating an optimized life insurance package includes the steps of collecting consumer data comprising an age and a risk class, determining a match between at least one life insurance policy and at least one Life Insurance Option, wherein the match is determined based at least partially on a period of coverage for the at least one life insurance policy and at least a portion of the consumer data, generating an optimized life insurance package comprising the at least one Life Insurance Option, and transmitting data configured to generate at least one graphical user interface comprising a visual representation of the optimized life insurance package. Other methods, systems, and computer program products are also disclosed.

Methods and apparatus, including computer program products, for securitizing natural catastrophe risk. One or more risk classes representing natural catastrophe risks is are established, and a first collection of risk instruments of a first risk class of the one or more risk classes is issued. Each risk class is recurringly issuable as risk instruments providing a return on an investment. The amount of the return for a risk instrument is contingent upon the occurrence of a realization event for the corresponding represented natural catastrophe risk. Collections of risk instruments issued from recurringly issuable risk classes are also described.

The invention discloses a grid-related power plant relay protection fixed value risk evaluation system based on an expert system. The grid-related power plant relay protection fixed value risk evaluation system is high in operability, high in efficiency and scientific and comprises building of a model, risk evaluation calculation, determination of the risk class and input / output of data.

A system and method for real-time risk-assessment and adjustment, risks associated with a plurality of risk exposed individuals being at least partially transferable from a risk exposed individual to a first insurance system and / or from the first insurance system to an associated second insurance system. The system including a table with retrievable stored risk classes each comprising assigned risk class criteria, individual-specific parameters of the risk exposed individuals being captured relating to criteria of the stored risk classes by the system and stored in a memory, and a specific risk class associated with the risk of the exposed individual being identified out and selected of the stored risk classes by the system based on the captured parameters.

The invention discloses a method for judging the floor water inrush risk degree of a deep well and belongs to the field of mine safety analysis. A plurality of main controlling factors affecting the floor water inrush are collected firstly, evaluation indexes are weighed and selected according to the main controlling factors, the subordinating degree function of the evaluation indexes is determined, a floor water inrush obvious case is selected by the combination of the practical floor water inrush condition, sample data of the floor water inrush are subjected to normalization processing, cases are classified by an MATLAB program, and a floor water inrush risk degree case data base is constructed; finally the evaluation index data of the to-be-tested floor water inrush risk degree are input to determine the to-be-tested floor water inrush risk class. The method can evaluate the plurality of main controlling factors, and technical support is provided for deep mine exploitation safety.

The invention discloses a fund portfolio recommendation method and device, equipment and a storage medium. The method comprises the steps of obtaining an investment behavior portrait of a user; determining a target risk tolerance level of the user according to the investment behavior portrait; obtaining the allocation proportion of the class assets in the lowest risk and the allocation proportion of the class assets in the highest risk; and determining a target fund portfolio according to the target risk tolerance level, the lowest risk class asset allocation proportion and the highest risk class asset allocation proportion, and recommending the target fund portfolio. Through the technical scheme of the invention, a personalized investment scheme can be specially customized for a user, the latest situation of the market can be continuously tracked, and timely dynamic adjustment is carried out on the asset allocation scheme, and fund combinations held by the user are continuously optimized.

The invention provides a selection method for a lightning protection device of a pole tower of a power distribution line, and belongs to the technical field of lighting protection. The selection method comprises the steps of determining a target circuit class and a safety request value I at a target circuit region; performing lightning stroke risk estimation on the pole tower to obtain a lightningstroke risk class and a lightning stroke weighted value m of the pole tower; performing quantitative evaluation on performance a lightning protection device; determining a lightning protection weighted value n of the lightning protection device; and determining a reference value g of the pole tower, performing technological economic evaluation on the lightning protection device according to the reference value g, the lightning stroke weighted value m, the lightning protection weighted value n and the safety request value I, and determining optimal lightning protection device. By the steps, the determined lightning protection device with low cost and good lightning protection performance is arranged on the pole tower connected with the power distribution line, so that the lightning protection performance of the power distribution line is accurately corresponding to local lightning protection demand, a power supply circuit is difficult to generate power failure even when lightning strikes weather, and daily and normal running of industrial production are not further affected.

Embodiments of the invention provide an anonymous RFQ system for financial instruments that resolves the inherent conflict between a capital provider's need for information and a market participant's need for confidentiality by creating an environment where market participants and capital providers can realize the benefits of sharing confidential trading interest (CTI) information without sacrificing anonymity or enabling information leakage. This secure environment preferably is created within an electronic matching book that distills all CTI information related to each Request for Quote (RFQ) into a risk class that is sent to capital providers in lieu of order-identifying or trader-identifying information. These risk classes give capital providers enough information to offer customized, risk-adjusted quotes without requiring the market participant to reveal confidential information about herself or her order.

A system and method for user created 2-dimensional risk classes and levels is described. These classes are implemented as a matrix of real numbers. In one embodiment, this matrix allows the user to create and select risk thresholds for the placement of bets that from an investment perspective can lead to the construction of a new type of financial instrument similar to low yield, low risk government issued bonds. In a second embodiment this is a zero-consideration contest where users compete at no cost for prizes to be awarded. In a third embodiment (and where it is legal to do so), this is a gambling application. The risk matrix is created and managed by the user and no one else. The construction of the matrix is described in detail. Included are computer runs that highlight important aspects of the invention.

A system and method for user created 2-dimensional risk classes and levels is described. In one embodiment, this matrix allows the user to create and select risk thresholds for the placement of bets that from an investment perspective can lead to the construction of a new type of financial instrument similar to low yield, low risk government issued bonds. In a second embodiment this is a zero-consideration contest where users compete at no cost for prizes to be awarded. In a third embodiment (and where it is legal to do so), this is a gambling application. The risk matrix is created and managed by the user and no one else. Included are computer runs that highlight important aspects of the invention. Finally, a tangible new game embodiment is described that replaces a standard Roulette table surface and wheel with new embodiments that implement the 2-dimensional risk classes described herein.